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Laser scanners in com-bination with accurate orientation devices are often used in Geometric Reverse Engineering (GRE) to measure point data. The industrial robot as a device for orientation has relatively low accuracy but the advantage of being numerically controlled, fast, and flexible and it is therefore of interest to investigate if it can be u...
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... Reverse Engineering (GRE) is concerned with the problem of creating CAD-models of real objects by fitting 3D point data measured from their surfaces. An introduction to GRE which is often 1 referred to is a paper by Varady [ ]. See 2 3 also [ ] and [ ]. Measurement systems for this purpose are often based on laser range finders in combination with mechanical devices for orientation. For industrial applications it is preferable that the orienting device is possible to control numerically, so that point clouds can be created without human interaction. This leads to the idea of using an industrial robot as the orienting device. To test this idea we have designed and built a measuring system based on a profile scanner and an industrial robot ABB IRB140 with a turntable see figure 1. To integrate the two systems and control the movement of the scanner, we use Varkon, 4 an open source CAD system; see [ ] and 5 [ ].With a measurement system of this kind, a point on the surface of an object ...
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Citations
... In order to improve the coverage of a scan pass at the surface of the object of interest, it will be placed on a rotary table, which is the 7 th degree of freedom to the scanning system. A similar setup was proposed by Rahayem et al. (2008), with a 810 mm reach of the robot arm and 30 µm repeatability, and a single-camera laser probe. ...
This article presents a heuristic algorithm for motion planning of a short range 7-DOF Laser Scanning System consisting of a 6-DOF vertical robot arm and a rotary table holding the workpiece. The redundancy of the mechanism is exploited for specifying certain constraints such as imposing a smooth motion of the rotary table while respecting the acceleration and speed limits and avoiding undesirable configurations of the robot arm such as the kinematic singularities, out-of-range conditions and collisions between the mechanical elements of the system (robot, table, workpiece and laser probe). The paper also presents the control system of the rotary table, and a communication protocol which allows the integration of the above-mentioned planning algorithm into the 3D scanning system.
... In order to improve the coverage of a scan pass at the surface of the object of interest, it will be placed on a rotary table, which is the 7 th degree of freedom to the scanning system. A similar setup was proposed by Rahayem et al. (2008), with a 810 mm reach of the robot arm and 30 µm repeatability, and a single-camera laser probe. ...
This article presents a heuristic algorithm for motion planning of a short range 7-DOF Laser Scanning System consisting of a 6-DOF vertical robot arm and a rotary table holding the workpiece. The redundancy of the mechanism is exploited for specifying certain constraints such as imposing a smooth motion of the rotary table while respecting the acceleration and speed limits and avoiding undesirable configurations of the robot arm such as the kinematic singularities, out-of-range conditions and collisions between the mechanical elements of the system (robot, table, workpiece and laser probe). The paper also presents the control system of the rotary table, and a communication protocol which allows the integration of the above-mentioned planning algorithm into the 3D scanning system.
... Segmentation and fitting is the third step in the GRE process according to Vàrady et al. [24]. We have implemented a method for planar segmentation, see [15], based on a curvature estimation method described by Sacchi et.al. [17], where a seed triangle is selected and a region growing algorithm is used to connect neighboring triangles that are coplanar. ...
Geometric Reverse Engineering (GRE) can be described as the process of fitting surfaces to point data and connecting them to topologically well defined CAD models. We have mounted a laser profile scanner on an industrial robot with a turntable and interfaced them to an Open Source CAD platform. With this tool we have developed an integrated system that can automatically plan and control the robot movements needed to measure an object of unknown shape. Details of this work have been published earlier but we have not described the platform used to integrate the hardware with the GRE software. This paper illustrates the multi disciplinary nature of that problem and investigates what the requirements are for a suitable CAD tool.
The paper presents a method and related algorithm for visual robot guidance in tracking objects moving on conveyor belts; the instantaneous location of the moving object is evaluated by a vision system consisting from a stationary, down looking monochrome video camera, a controller-integrated image processor and a vision extension of the structured V+ robot programming environment. The algorithm for visual tracking of the conveyor belt for "on-the-fly" object grasping is partitioned in two stages: (i) visual planning of the instantaneous destination of the robot, (ii) dynamic re-planning of the robot's destination while tracking the object moving on the conveyor belt. The control method uses in addition the concept of Conveyor Belt Window — CBW. The paper discusses in detail the motion control algorithm for visually tracking the conveyor belt on which objects are detected, recognised and located by the vision part of the system. Experiments are finally reported in what concerns the statistics of object locating errors and motion planning errors function of the size of the objects and of the belt speed. These tests have been carried out on a 4-d.o.f. SCARA robot with artificial vision and the AVI AdeptVision software extension of the V+ high-level, structured programming environment.
Industrialapplicationslikerobot-aidedwelding,automatedinspection,and3Dmeasurementsrequire
3D pointstobecapturedfromthesurfacesofobjectsandprocessedtocalculatetheinformation-of-
interest.Thelackofresearchfocusedonfittingellipsesto3Dlaserprofiledata,andtheintrinsic
featuresthatdistinguishitfrom2Ddigitalimages,motivatedustoconductacomparativestudy
involvingthemostpopularellipse-fittingmethods.Afterdescribingourlaserprofilescanningsystem,
and asurveyofellipse-fittingmethods,wecompare,usingextensiveexperimentsperformedwith
syntheticandrealdata,thefittingalgorithmsintermsofstabilityandaccuracywithrespecttoavariety
of factors.Theestimateobtainedwiththebestmethodisusedtoinitializearobustnon-lineariterative
ellipsefittingmethod.Finally,wedescribeanovelmethodfortheconstructionofcylindricalsurfaces
from estimatedellipticalsections.
Applications like geometric reverse engineering, robot vision and automatic inspection require sets of points to be measured from the surfaces of objects and then processed by segmentation and fitting algorithms to establish shape parameters of interest. In industrial applications where speed, reliability and automatic operation is of interest a measuring system based on a laser profile scanner mounted on an industrial robot can be of interest. In earlier publications we have presented such a system and also a segmentation algorithm for planar surfaces using 2D profile data in combination with robot poses. Due to the data reduction offered by this approach the segmentation algorithm computes faster than algorithms based on 3D point sets alone. Encouraged by the results we have now developed a segmentation algorithm for two different quadric surfaces also based on 2D profiles in combination with robot poses. This paper presents the new algorithm together with test results and also an interesting observation that points to future work.
